Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Despite high mortality rates, surprisingly little research has been done to study chronic kidney disease (CKD) patients' preferences for end-of-life care. The objective of this study was to evaluate end-of-life care preferences of CKD patients to help identify gaps between current end-of-life care practice and patients' preferences and to help prioritize and guide future innovation in end-of-life care policy. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: A total of 584 stage 4 and stage 5 CKD patients were surveyed as they presented to dialysis, transplantation, or predialysis clinics in a Canadian, university-based renal program between January and April 2008. RESULTS: Participants reported relying on the nephrology staff for extensive end-of- life care needs not currently systematically integrated into their renal care, such as pain and symptom management, advance care planning, and psychosocial and spiritual support. Participants also had poor self-reported knowledge of palliative care options and of their illness trajectory. A total of 61% of patients regretted their decision to start dialysis. More patients wanted to die at home (36.1%) or in an inpatient hospice (28.8%) compared with in a hospital (27.4%). Less than 10% of patients reported having had a discussion about end-of-life care issues with their nephrologist in the past 12 months. CONCLUSIONS: Current end-of-life clinical practices do not meet the needs of patients with advanced CKD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".